While advances in development of successful cancer therapies progress, only a subset of patients respond to any particular therapy. With the narrow therapeutic index and the toxic potential of many available cancer therapies, such differential responses potentially contribute to patients undergoing unnecessary, ineffective and even potentially harmful therapy regimens.
One way to optimize therapy to treat individual patients is to determine whether one or more predictors correlate with a particular outcome in response to therapy. The ability to predict drug sensitivity in patients is particularly challenging because drug responses reflect both the properties intrinsic to the target cells and also a host's metabolic properties.
There is a need to identify further predictive markers to identify particular cancer patients who are expected to have a favorable outcome when administered particular cancer therapies. There is also a further need to identify assays useful for determining presence of more than one biomarker in a sample at once.